Abstract
Hail is one of the risks that most frightens farmers and one of the few currently insured climatic-related phenomena. In the last years, a significant increase occurred of adverse events affecting crops, highlighting that ordinary strategies of insurance companies should migrate to a more dynamic management. In this work a prototype of service based on remotely sensed data is presented aimed at supporting evaluation of hail impacts on crops by mapping and qualifying areas damaged by hail. Further, a comparison was done testing effectiveness of approaches based on short term (i.e. with reference to images acquired immediately after the event) and long term (i.e. with reference to images acquired close to crop harvest) analysis. Investigation was solicited by the Reale Mutua insurance company and focused on a strong hailstorm occurred on 6th July 2019 in the Vercelli province (Piemonte - NW Italy). The analysis was based on Copernicus Sentinel-2 level 2A imagery. A times series made of 29 NDVI maps was generated for the growing season 2019 (from March to October) and analyzed at pixel level looking for NDVI trend anomalies possibly related to crop damages. Phenological behavior of damaged crops (NDVI local temporal profile) was compared with those of unharmed fields to verify and assess the impact of the phenomenon. Results showed evident anomalies along the local NDVI temporal profile of damaged cropped pixels, permitting a fine mapping of the affected areas. Surprisingly, short and long term approaches led to different conclusions: some areas, appearing significantly damaged immediately after the event, showed a vegetative recover with the proceeding of the growing season (temporary damages). Differently, some others showed that damages detected after the events never turned into a better situation (permanent damages). This new information could drive to considered a revision of the ordinary insurance procedures that are currently used by companies to certify and quantify damages of crops after adverse events. It can therefore said that, the high temporal resolution of the Copernicus Sentinel 2 mission can significantly contribute to improve evaluating procedures in the insurance sector by introducing temporal variables.
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Authors would like to thank Reale Mutua for supplying all needed ground data and maps to achieve the tasks of this works.
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Sarvia, F., De Petris, S., Borgogno-Mondino, E. (2020). A Methodological Proposal to Support Estimation of Damages from Hailstorms Based on Copernicus Sentinel 2 Data Times Series. In: Gervasi, O., et al. Computational Science and Its Applications – ICCSA 2020. ICCSA 2020. Lecture Notes in Computer Science(), vol 12252. Springer, Cham. https://doi.org/10.1007/978-3-030-58811-3_53
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